Transcriptome data-based screening of potential host of genetic transformation for a blue-hued Bougainvillea transgene.

Bougainvillea is a popular ornamental plant. Although Bougainvillea is abundant in germplasm resources, cultivars and flower colors, there is no rare blue colour varieties, due to the absence of delphinidin-based anthocyanins. This study analyzed the Bougainvillea leaf and bract transcriptome to select hosts of genetic transformation that would be suitable for the accumulation of delphinidin. A total of 36 gigabyte (GB) of raw data was obtained by transcriptome sequencing, with 4,058 significantly differentially expressed genes, including 1,854 upregulated and 2,204 downregulated genes. Annotation of these genes was performed using Gene Ontology and Kyoto Encyclopedia of Genes and Genomes databases. Through annotation, two CHS genes, one F3H gene, one DFR gene, and one F3'H gene involved in the delphinidin biosynthesis pathway were identified. The expression levels of these genes and total flavonoid content in the bracts of six Bougainvillea varieties were examined through quantitative real-time PCR and spectrophotometry, respectively. Through the comprehensive evaluation based on membership function method, the suitable host order for a blue-hued Bougainvillea transgene is Singapore White>Elizabeth Angus>Ratana Yellow>China Beauty>Orange King>Brilliant Variegata. Thus, Singapore White variety was the most appropriate transgene host for blue-hued Bougainvillea. The results of this study provide a reference for the directed breeding of blue-hued Bougainvillea.

Integration of the metabolome and transcriptome reveals the molecular mechanism of drought tolerance in Plumeria rubra.

Plumeria rubra L. cv. Acutifolia is an ornamental tree that displays a good drought-tolerance level. However, the molecular mechanisms of P. rubra adaptation to drought stress remains unclear. Here, drought-simulating pot experiments were conducted to explore drought stress response mechanism of P. rubra. Transcriptome analysis revealed 10,967 differentially expressed genes (DEGs), 6,498 of which were increased and 4,469 decreased. Gene Ontology (GO) analysis revealed that the DEGs were enriched in binding category, in metabolic process category, and in catalytic activities category. The Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis showed that 9 pathways were significantly enriched, including biosynthesis of secondary metabolites (ko01110), plant hormone signal transduction (ko04075) and so on. In addition, the transcription factor families of AP2/ERFs, bZIP, and C2H2 were significantly upregulated while the families of bHLH, MYB-related, and NAC were significantly downregulated. Moreover, the results of metabolomics analysis indicated that some compounds were accumulated under drought stress, especially flavonoids. Overall, it was speculated that under drought stress, P. rubra first activates the plant hormone signal transduction pathway to regulate hormone contents. Then osmotic regulating substances such as organic acids and amino acids are accumulated to maintain osmotic balance. Finally, flavonoid levels are increased to scavenge reactive oxygen species. These results preliminarily revealed the molecular mechanisms adopted by P. rubra in response to drought stress.

The influence of subjective well-being on mental health in nursing students: the role of student cynicism.

Previous studies have reported high rates of poor mental health among nursing students, but few studies focused on the internal pathway of mental health. This cross-sectional study was conducted at a vocational medical school and investigated 384 nursing students. Symptom Check List-90, Index of Well-Being Scale and Cynical Attitudes Toward College Scale were used to test mental health, subjective well-being (SWB) and cynicism of nursing students, respectively. Academic cynicism, social cynicism and institutional cynicism were negatively related to mental health. SWB not only directly had positive effect on mental health, but had an indirect effect on mental health through academic cynicism, social cynicism and institutional cynicism.

Deep learning to diagnose Hashimoto's thyroiditis from sonographic images.

Hashimoto's thyroiditis (HT) is the main cause of hypothyroidism. We develop a deep learning model called HTNet for diagnosis of HT by training on 106,513 thyroid ultrasound images from 17,934 patients and test its performance on 5051 patients from 2 datasets of static images and 1 dataset of video data. HTNet achieves an area under the receiver operating curve (AUC) of 0.905 (95% CI: 0.894 to 0.915), 0.888 (0.836-0.939) and 0.895 (0.862-0.927). HTNet exceeds radiologists' performance on accuracy (83.2% versus 79.8%; binomial test, p < 0.001) and sensitivity (82.6% versus 68.1%; p < 0.001). By integrating serologic markers with imaging data, the performance of HTNet was significantly and marginally improved on the video (AUC, 0.949 versus 0.888; DeLong's test, p = 0.004) and static-image (AUC, 0.914 versus 0.901; p = 0.08) testing sets, respectively. HTNet may be helpful as a tool for the management of HT.

Improved diagnosis of thyroid cancer aided with deep learning applied to sonographic text reports: a retrospective, multi-cohort, diagnostic study.

OBJECTIVE: Large volume radiological text data have been accumulated since the incorporation of electronic health record (EHR) systems in clinical practice. We aimed to determine whether deep natural language processing algorithms could aid radiologists in improving thyroid cancer diagnosis. METHODS: Sonographic EHR data were obtained from the EHR database. Pathological reports were used as the gold standard for diagnosing thyroid cancer. We developed thyroid cancer diagnosis based on natural language processing (THCaDxNLP) to interpret unstructured sonographic text reports for thyroid cancer diagnosis. We used the area under the receiver operating characteristic curve (AUROC) as the primary metric to measure the performance of the THCaDxNLP. We compared the performance of thyroid ultrasound radiologists aided with THCaDxNLP vs. those without THCaDxNLP using 5 independent test sets. RESULTS: We obtained a total number of 788,129 sonographic radiological reports. The number of thyroid sonographic data points was 132,277, 18,400 of which were thyroid cancer patients. Among the 5 test sets, the numbers of patients per set were 439, 186, 82, 343, and 171. THCaDxNLP achieved high performance in identifying thyroid cancer patients (the AUROC ranged from 0.857-0.932). Thyroid ultrasound radiologists aided with THCaDxNLP achieved significantly higher performances than those without THCaDxNLP in terms of accuracy (93.8% vs. 87.2%; one-sided t-test, adjusted P = 0.003), precision (92.5% vs. 86.0%; P = 0.018), and F1 metric (94.2% vs. 86.4%; P = 0.007). CONCLUSIONS: THCaDxNLP achieved a high AUROC for the identification of thyroid cancer, and improved the accuracy, sensitivity, and precision of thyroid ultrasound radiologists. This warrants further investigation of THCaDxNLP in prospective clinical trials.

Prevalence of and factors related to anxiety and depression symptoms among married patients with gynecological malignancies in China.

OBJECTIVE: This study aims to investigate the prevalence of anxiety and depression among married patients with gynecological malignancies in China and then explores factors related to anxiety and depression. METHODS: A cross-sectional study was conducted from July 2016 to July 2017 in Jilin Province. A total of 394 married patients with gynecological malignancies completed the Hospital Anxiety and Depression Scale (HADS). Univariate analysis and multivariate logistic regression analysis were used to evaluate the association between influencing factors of anxiety and depression. Back propagation neural networks (BP neural networks) were used to examine the ranking of these influencing factors. RESULTS: The prevalence of anxiety and depression was 79.95% and 94.16% in married patients with gynecological malignancies. Multivariate logistic analysis revealed that patients' anxiety showed significant relationships with low income, frequency of chemotherapy, diagnostic results and low sleep quality(P < 0.05), and patients' depression showed significant relationships with low quality sleep and frequency of chemotherapy (P < 0.05). Using BP neural networks, the order of importance of these factors in influencing anxiety, from high to low, was determined to be sleep quality, frequency of chemotherapy, monthly income, diagnostic results, age and fertility demand. CONCLUSIONS: It is important to reduce anxiety and depression in these patients by improving sleep quality and clinical treatment.

Association between parental marital conflict and Internet addiction: A moderated mediation analysis.

BACKGROUND: The effect of parental marital conflict on Internet addiction has been well-established; however, little is known regarding the underlying mechanism of this effect. The aim of this study was to explore the mediating effect of depression and anxiety, as well as the role of peer attachment as a moderator in this relation between parental marital conflict and Internet addiction. METHODS: The moderated mediation analysis was tested using data from a cross-sectional sample of 2259 high school students who completed questionnaires regarding marital conflict, depression, anxiety, peer attachment and Internet addiction. RESULTS: The results indicated that the effect of parental marital conflict on Internet addiction was mediated by depression and anxiety. In addition, peer attachment moderated the association between parental marital conflict and depression/anxiety. CONCLUSIONS: This study helps to elucidate the mechanism underlying the association between parental marital conflict and Internet addiction.

The influence of alexithymia on mobile phone addiction: The role of depression, anxiety and stress.

BACKGROUND: Alexithymia is an important predictor of mobile phone addiction. Enhancing and improving college students' mental health can reduce the rate of mobile phone addiction. However, it is not clear about the role of depression, anxiety and stress in the relationship between college students' alexithymia and mobile phone addiction. METHODS: A total of 1105 college students were tested with the Toronto Alexithymia Scale, the Depression Anxiety Stress Scale and the Mobile Phone Addiction Index. RESULTS: An individual's level of alexithymia was significantly correlated with depression, anxiety, stress and mobile phone addiction. Alexithymia had a significantly positive prediction effect on mobile phone addiction, and depression, anxiety, and stress on mobile phone are positive predictors. Depression, anxiety or stress had partially mediating effects between alexithymia and mobile phone addiction. Alexithymia not only directly had a positively impact on mobile phone addiction, but both also had an indirect effect on mobile phone addiction through depression, anxiety or stress. LIMITATIONS: Limitations included sampling method and modest sample size, self-report measures, and unmeasured potential confounders. CONCLUSION: Alexithymia is an important correlate of mobile phone addiction, and depression, anxiety or stress is an important mediator in this relationship.

Prevalence and Correlates of Suicidal Behaviors among College Students in Northeastern China: a Cross-Sectional Study.

The present study aimed to investigate the prevalence and correlates of suicidal behaviors among college students in Jilin Province, China. A cross-sectional survey was conducted in 2016, using a self-reported questionnaire. Convenience sampling method was used to select college students as participants. The analysis was based on a sample of 730 college students. We use multivariate logistic model to determine the risk factors of suicidal behaviors.The prevalence of suicidal ideation, suicidal plan, suicidal attempts were respectively 13.2%, 3.3% and 3.4%. After controlling for the potential confounding factors, history of family psychiatric illness, depression and quality of life were significantly associated with suicidal ideation. Besides, suicidal plan was predicted significantly by not living together with university roommates and depression. In terms of suicidal attempts, not living together with university roommates and history of family psychiatric illness were its risk factors. Comprehensive interventions regarding aims at risk factors may be critical as effective strategies to protect college students from suicide.

A comparative study of negative life events and depressive symptoms among healthy older adults and older adults with chronic disease.

OBJECTIVE: This study aims to study internal relations and functionary mechanism between social support, coping style, negative life events and depressive symptoms and compare these relations in healthy older adults and older adults with chronic disease. DESIGN: A cross-sectional study was conducted in 2015. In total, 1,264 older adults with chronic disease and 749 healthy older adults participated in this investigation which consist of socio-demographic characters, negative life events, social support, coping style and depressive symptoms. RESULTS: The path and direction of variable function in healthy older adults were inconsistent with older adults with chronic disease. Older adults with chronic disease had more severe depressive symptoms and negative life events, and lower social support and positive coping style. Negative life events, subjective support, positive coping style and negative coping style were significantly predicted depressive symptoms. Objective support may weaken the influence of negative life events on depressive symptoms in chronic disease group. Utilization of support and positive coping style worsen the effect of negative life events on depressive symptoms in healthy older adults. CONCLUSION: This study implied that to improve their mental health, attention should be paid to the role of biological, psychological and social stress factors and its inherent law of interaction.

Improving air pollution control policy in China--A perspective based on cost-benefit analysis.

To mitigate serious air pollution, the State Council of China promulgated the Air Pollution Prevention and Control Action Plan in 2013. To verify the feasibility and validity of industrial energy-saving and emission-reduction policies in the action plan, we conducted a cost-benefit analysis of implementing these policies in 31 provinces for the period of 2013 to 2017. We also completed a scenario analysis in this study to assess the cost-effectiveness of different measures within the energy-saving and the emission-reduction policies individually. The data were derived from field surveys, statistical yearbooks, government documents, and published literatures. The results show that total cost and total benefit are 118.39 and 748.15 billion Yuan, respectively, and the estimated benefit-cost ratio is 6.32 in the S3 scenario. For all the scenarios, these policies are cost-effective and the eastern region has higher satisfactory values. Furthermore, the end-of-pipe scenario has greater emission reduction potential than energy-saving scenario. We also found that gross domestic product and population are significantly correlated with the benefit-cost ratio value through the regression analysis of selected possible influencing factors. The sensitivity analysis demonstrates that benefit-cost ratio value is more sensitive to unit emission-reduction cost, unit subsidy, growth rate of gross domestic product, and discount rate among all the parameters. Compared with other provinces, the benefit-cost ratios of Beijing and Tianjin are more sensitive to changes of unit subsidy than unit emission-reduction cost. These findings may have significant implications for improving China's air pollution prevention policy.